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Publication Additional Information Download
Publication Type
Conference Poster
Authorship
Harder P., Marsh C.B., and Pomeroy J.W.
Title
Distributed modelling of the Canadian Prairie snowpack: model evaluation and demonstration
Year
2023
Publication Outlet
CGU2023
Citation
Harder P., Marsh C.B., and Pomeroy J.W. (2023). Distributed modelling of the Canadian Prairie snowpack: model evaluation and demonstration. CGU2023. https://www.chrismarsh.ca/cgu2023
Abstract
Background
•Canadian Prairie snowmelt generates most annual runoff to creeks and wetlands and infiltrates to replenish the soil water reserves necessary for crop growth
•Snowmelt volume is governed by over-winter snow accumulation, wind redistribution, and sublimation by blowing snow
•Blowing snow redistribution is strongly affected by vegetation and topography
•There is a large gap in the capacity to remotely sense or model the snow processes on the prairies at snow-drift permitting scales for large spatial scales

Objectives
•Evaluate the ability to model the spatial variability of snow accumulation, redistribution, and ablation on the Canadian Prairies at a high spatial resolution
•Identify and inform the model development needs to support near real-time prairie-wide prediction of snowpack at sub-field scale

Methodlogy
100 ha study site at the Clavet Livestock and Forage Centre for Excellence near Saskatoon — part of Global Water Futures Observatories
•Simulated snow accumulation, redistribution, and ablation processes at a 3 m resolution with the Canadian Hydrological Model (CHM)
•Blowing snow redistribution simulated with PBSM3D, snow energetics with Factorial Snow Model (FSM), and small-scale windfields with Windmapper
•Topography resolved from UAV-lidar digital elevation model
•Constant 0.3 m vegetation height
•Driven by both local meteorological observations and ECCC’s High Resolution Deterministic Prediction System (HRDPS) data from Nov 1, 2022 to April 24, 2023

Conclusion
-The first high-resolution application of PBSM3D in Canadian Prairies simulated key topographic aspects of snow redistribution to depressions
-Further refinement of vegetation-wind interactions and the effect of ice layers on transport thresholds will improve estimates of snow erodibility
-HRDPS had a low wind speed bias that restricted redistribution
Program Affiliations
GWF: Global Water Futures
Project Affiliations
GWF-CORE: Core Modelling and Forecasting
GWF-CS: Computer Science
GWF-TSTSW: Transformative Sensor Technologies and Smart Watersheds
Publication Stage
Published
Download Links
https://chrismarsh.ca/cgu2023/files/PrairieSnow_CGU2023.pdf

Poster:
https://www.chrismarsh.ca/cgu2023/#poster

See animation:
https://www.chrismarsh.ca/cgu2023/#animation

Model:
https://www.chrismarsh.ca/cgu2023/#CHM
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